Published

AI Companion Evaluation Framework

Audited multilingual character catalog, benchmark protocols, and developer-ready feeds for Japanese, Korean, Spanish, Portuguese, and Chinese AI companion research.

AI Companion Evaluation Framework

A useful AI companion review should describe observable behavior instead of relying on a single overall score. The open benchmark separates five evidence dimensions.

Dimensions

DimensionSuggested evidence
Character consistencyRepeated prompts across a defined conversation window
Memory continuityRecall checks with elapsed turns documented
Instruction controlStyle, boundary, and correction prompts
Image identity stabilityRepeated image prompts with the same character brief
Localization qualityNative-language prompts reviewed by fluent speakers

Test record

For each result, record the date, model or product state, locale, prompt class, sample size, and any exclusions. Screenshots can illustrate an observation, but the written method should remain understandable without them.

Character creation tests can begin with the Ponys.ai character generator. Image consistency tests should use the AI image generator, and continuity tests should clearly distinguish chat behavior from AI video generation.

Responsible interpretation

Do not present a first-party benchmark as an independent ranking. Publishers should reproduce the method, retain contradictory results, and explain the limits of small samples. Adult-oriented evaluations should also document age gates, consent boundaries, privacy behavior, and regional availability.